Refining A-Share Reversal with Single-Trade Amount Sorting

Summary

This research report proposes improving a conventional stock reversal signal by splitting each stock’s recent daily returns according to average trade size. For each lookback window, it ranks days by daily turnover divided by trade count, compounds returns separately for the upper and lower halves, then subtracts the lower-group return from the higher-group return. The premise is that returns on days with larger average trades exhibit stronger reversal, while the other group can show weaker reversal or momentum.

The report evaluates the factor on Chinese A-shares from 2010 to 2018, excluding special-treatment stocks and recent listings. It reports stronger factor statistics and long-short results than a standard 20-day reversal measure, and also describes tests across other lookbacks and stock universes, style and industry residualization, and alternative group splits. The evidence is historical and presented with caveats: factor behavior may change, and the report’s discussion of trading behavior is an interpretation rather than proof of causality. It does not establish that the reported results will persist after live trading costs or future market changes.

Key ideas

• The method ranks each stock’s recent trading days by average transaction amount, calculated from turnover and trade count.
• It compounds returns separately for the high and low average-trade-amount groups and differences the two results.
• The report attributes stronger reversal to returns from days with larger average trades.
• Historical tests cover multiple lookbacks and A-share universes, including style and industry residualization.
• The authors caution that results use historical data and may not persist in changed markets.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.